Automated Data (ADI), an AI-powered data matching & mastering platform announced the launch of AutoMatch, responding to market demand for an easy to use tool that connects siloed data. With AutoMatch, clients will be able to automatically generate matching pipelines utilizing ADI’s out-of-the-box models and AI-driven semantic profiling engine–removing the need for users to understand data matching techniques. This product launch represents a significant milestone towards achieving ADI’s vision to automatically connect a company’s entire data environment into a usable knowledge asset.
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“Automated Data’s no-code platform and the AutoMatch product promises to change how data is connected, completely modernizing entity resolution and mastering to drive quick insights and solve real-world problems,” said Michael Rude, ADI CEO. “The out-of-the-box solution eliminates the need for data teams to analyze documentation, design and build complex integration processes by automating the entire process, providing the necessary recommendations to get to a 360 degree view of your data faster.”
Once your existing data is connected to the ADI platform, AutoMatch can be triggered to calculate statistics and identify the semantic types of your data across databases and tables. The semantic types are inferred by our proprietary ML model designed to identify data regardless of data type or field name. There are numerous categories of semantic understanding, including market data, geospatial, a specific pattern such as email address, dates or recurring patterns in data such as hyphenated phrases.
With a clear and contextual understanding of the data, ADI automatically selects the models, sequences and routines required to achieve high fidelity matching.
“The problem of data silos and disparate data has been talked about for years. ADI’s platform solves the problem of connecting data in minutes no matter where your data is,” said Adam Cardarelli, ADI Chief Product Officer. “You can write more efficient queries, lower your data infrastructure spend and achieve better business outcomes in a fraction of the time.”
“The next leg of our journey will be to help customers automatically generate knowledge graphs from their data. Establishing the next generation of knowledge graphs will be a foundational component for any AI-driven strategy, ensuring only high-quality, fact-based information is powering your models,” continued Rude. “We are building a platform to become a critical and unique component of every company’s data infrastructure.”
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Automated Data covers a wide variety of matching use cases, from entity resolution, taxonomy classifications, schemas, etc. on structured and unstructured data. The platform connects data together no matter where the data is stored, so there are no costly data migration projects required or delays in getting the highest return on investment with new datasets coming to market.
“While there is no silver bullet for matching, our platform is one of the first to allow clients the flexibility to use every approach at their disposal, including their own internal models, 3rd party models, and ADI’s out-of-the-box models to address matching problems that cannot typically be addressed by the existing MDM or data integration market. Matching processes are then supported by human-in-the-loop workflows, lineage, override tracking and a suite of other capabilities that no data science or engineering team wants to build,” said Jason Taylor, ADI Head of Data.
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